Triple

T12274046
Position Surface form Disambiguated ID Type / Status
Subject El Golf E292543 entity
Predicate hasStationCode P1289 FINISHED
Object EGF
EGF is the station code for El Golf, a metro station in Santiago, Chile.
 E974759 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: EGF | Statement: [El Golf, hasStationCode, EGF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EGF
Context triple: [El Golf, hasStationCode, EGF]
  • A. EGF
    EGF is the ICAO airline designator used to identify American Eagle Airlines in aviation operations and communications.
  • B. EGF
    EGF is a European Union financial instrument that supports workers who lose their jobs due to major structural changes in world trade patterns or economic crises.
  • C. EGFR
    EGFR (epidermal growth factor receptor) is a transmembrane receptor tyrosine kinase that regulates cell growth and survival and is frequently implicated in cancer development and progression.
  • D. HGF
    HGF is the abbreviation for the Helmholtz Association, Germany’s largest scientific research organization spanning multiple disciplines and large-scale facilities.
  • E. HGF
    HGF is the National Rail station code for Hag Fold railway station in Greater Manchester, England.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: EGF
Triple: [El Golf, hasStationCode, EGF]
Generated description
EGF is the station code for El Golf, a metro station in Santiago, Chile.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EGF
Target entity description: EGF is the station code for El Golf, a metro station in Santiago, Chile.
  • A. EGF
    EGF is the ICAO airline designator used to identify American Eagle Airlines in aviation operations and communications.
  • B. EGF
    EGF is a European Union financial instrument that supports workers who lose their jobs due to major structural changes in world trade patterns or economic crises.
  • C. EGFR
    EGFR (epidermal growth factor receptor) is a transmembrane receptor tyrosine kinase that regulates cell growth and survival and is frequently implicated in cancer development and progression.
  • D. HGF
    HGF is the abbreviation for the Helmholtz Association, Germany’s largest scientific research organization spanning multiple disciplines and large-scale facilities.
  • E. HGF
    HGF is the National Rail station code for Hag Fold railway station in Greater Manchester, England.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cef684081908adaee8e04facc2e completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e6b50a48190b1beabd149d5830f completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f61f9386548190a749445a404db3a2 completed May 2, 2026, 4 p.m.
NED2 Entity disambiguation (via description) batch_69f6207f164c8190b663a50ee3c761d6 completed May 2, 2026, 4:04 p.m.
Created at: April 8, 2026, 9:52 p.m.